Clinically important traits - such as susceptibility to disease and response to therapy - vary in the population and are influenced by inheritance. With the sequencing of the human genome and development of high throughput methods for studying genetic variation, there is great interest in trying to relate inherited differences in genome sequence to medically relevant outcomes. Developing methods to collect, analyze and apply such data to important human diseases is in its infancy, and yet of great potential. One challenge to progress is the requirement for insights and methods drawn from many fields, including clinical medicine, human genetics, epidemiology, genomics, statistical genetics, quantitative trait mapping, and population genetics. A major problem is that these disciplines generally operate in isolation, and thus there are few opportunities for investigators to interact together, compare perspectives, and develop novel approaches that synthesize these approaches. The goal of this Keystone Meeting is to bring together leading investigators from these different fields, and jointly to debate many of the important methodologic and scientific issues in the genetic analysis of human disease. Sessions will cover fundamental issues in human population genetics (patterns of genetic variation, determinants of mutation rates and recombination, and human population history) and application to disease gene mapping (technologies for genotyping and sequencing, statistical genetic analysis, epidemiological principles, impact of population demography, and lessons from successful projects). In addition, the conference will run concurrently with the "Natural Variation and Quantitative Genetics in Model Organisms" meeting, including joint sessions and meals. The explicit goal is to bring together investigators from each of the relevant communities (both in humans and model systems), to highlight the similarities and differences in perspectives, and to engage the problem of complex trait genetics and its application to human disease.